Vertical mixing of commercial aviation emissions from cruise altitude to the surface

Whitt, Daniel B.; Jacobson, Mark Z.; Wilkerson, Jordan; Naiman, A. D.; Lele, Sanjiva K.

doi:10.1029/2010jd015532

Cited by 28 publications

(29 citation statements)

References 51 publications

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“…So the NO x perturbation in low troposphere shown in Fig. 5 is not due to vertical transport, also found in the analyses by Whitt et al (2011). Figure 7 shows that the O 3 perturbation also weakens with decreased altitude.…”

Section: Changes In Gases (No Y and O 3 )supporting

confidence: 48%

“…For example, the time scale of vertical mixing from cruise altitudes to the boundary layer is longer than the lifetime of chemicals affected by non-LTO emissions (Whitt et al, 2011). So it is questionable that sinking motions in the mean general circulation of the atmosphere can effectively transport aircraft emissions down to the ground as suggested in Barrett et al (2010).…”

Section: Introductionmentioning

confidence: 99%

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Impacts of aircraft emissions on the air quality near the ground

et al. 2013

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The continuing increase in demand for commercial aviation transport raises questions about the effects of resulting emissions on the environment. The purpose of this study is to investigate, using a global chemistry transport model, to what extent aviation emissions outside the boundary layer influence air quality in the boundary layer. The large-scale effects of current levels of aircraft emissions were studied through comparison of multiple simulations allowing for the separated effects of aviation emissions occurring in the low, middle and upper troposphere. We show that emissions near cruise altitudes (9–11 km in altitude) rather than emissions during landing and take-off are responsible for most of the total odd-nitrogen (NO_y), ozone (O₃) and aerosol perturbations near the ground with a noticeable seasonal difference. Overall, the perturbations of these species are smaller than 1 ppb even in winter when the perturbations are greater than in summer. Based on the widely used air quality standards and uncertainty of state-of-the-art models, we conclude that aviation-induced perturbations have a negligible effect on air quality even in areas with heavy air traffic. Aviation emissions lead to a less than 1% aerosol enhancement in the boundary layer due to a slight increase in ammonium nitrate (NH₄NO₃) during cold seasons and a statistically insignificant aerosol perturbation in summer. In addition, statistical analysis using probability density functions, Hellinger distance, and p value indicate that aviation emissions outside the boundary layer do not affect the occurrence of extremely high aerosol concentrations in the boundary layer. An additional sensitivity simulation assuming the doubling of surface ammonia emissions demonstrates that the aviation induced aerosol increase near the ground is highly dependent on background ammonia concentrations whose current range of uncertainty is large

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Section: Changes In Gases (No Y and O 3 )supporting

confidence: 48%

Section: Introductionmentioning

confidence: 99%

Impacts of aircraft emissions on the air quality near the ground

et al. 2013

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“…Cross-polar aircraft flight is also an important contributor to the Arctic BC. Whitt et al (2011) (Fig. 5), in comparison to previous version mentioned in Shindell et al (2008), but still has significant underestimation in winter and spring, especially at Barrow station, where the bias can be up to one order of magnitude.…”

Section: Intercomparison Between Model Results and Observationsmentioning

confidence: 95%

The distribution of snow black carbon observed in the Arctic and compared to the GISS-PUCCINI model

et al. 2012

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Abstract. In this study, we evaluate the ability of the latest NASA GISS composition-climate model, GISS-E2-PUCCINI, to simulate the spatial distribution of snow BC (sBC) in the Arctic relative to present-day observations. Radiative forcing due to BC deposition onto Arctic snow and sea ice is also estimated. Two sets of model simulations are analyzed, where meteorology is linearly relaxed towards National Centers for Environmental Prediction (NCEP) and towards NASA Modern Era Reanalysis for Research and Applications (MERRA) reanalyses. Results indicate that the modeled concentrations of sBC are comparable with presentday observations in and around the Arctic Ocean, except for apparent underestimation at a few sites in the Russian Arctic. That said, the model has some biases in its simulated spatial distribution of BC deposition to the Arctic. The simulations from the two model runs are roughly equal, indicating that discrepancies between model and observations come from other sources. Underestimation of biomass burning emissions in Northern Eurasia may be the main cause of the low biases in the Russian Arctic. Comparisons of modeled aerosol BC (aBC) with long-term surface observations at Barrow, Alert, Zeppelin and Nord stations show significant underestimation in winter and spring concentrations in the Arctic (most significant in Alaska), although the simulated seasonality of aBC has been greatly improved relative to earlier model versions. This is consistent with simulated biases in vertical profiles of aBC, with underestimation in the lower and middle troposphere but overestimation in the upper troposphere and lower stratosphere, suggesting that the wet removal processes in the current model may be too weak or that vertical transport is too rapid, although the simulated BC lifetime seems reasonable. The combination of observations and modeling provides a comprehensive distribution of sBC over the Arctic. On the basis of this distribution, we estimate the decrease in snow and sea ice albedo and the resulting radiative forcing. We suggest that the albedo reduction due to BC deposition presents significant space-time variations, with highest mean reductions of 1.25 % in the Russian Arctic, which are much larger than those in other Arctic regions (0.39 % to 0.64 %). The averaged value over the Arctic north of 66°N is 0.4-0.6 % during spring, leading to regional surface radiative forcings of 0.7, 1.1 and 1.0 W m −2

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“…Satellite-derived fields of the relative humidity over ice at 200 hPa, contrail cloud fraction, and in-situ vertical profiles of black carbon, temperature, and dew point were compared with the model in Jacobson et al [2011]. Whitt et al [2011] compared zonally-averaged static stability and tropopause height from satellite data with the model. The comparison of model results with vertical profile data in these studies suggests a lack of numerical diffusion with respect to vertical transport of gases and particles in the model.…”

Section: Model Descriptionmentioning

confidence: 99%

Effects of Urban Surfaces and White Roofs on Global and Regional Climate

2012

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Abstract. Land use, vegetation, albedo, and soil-type data are combined in a global model that accounts for roofs and roads at near their actual resolution to quantify the effects of urban surface and white roofs on climate. In 2005, ~0.128% of the Earth's surface contained urban landcover, half of which was vegetated. Urban landcover was modeled over 20 years to increase gross global warming (warming before cooling due to aerosols and albedo change are accounted for) by 0.06-0.11 K and population-weighted warming by 0.16-0.31 K, based on two simulations under different conditions. As such, the urban heat island (UHI) effect may contribute to 2-4% of gross global warming, although the uncertainty range is likely larger than the model range presented, and more verification is needed. This may be the first estimate of the UHI effect derived from a global model while considering both UHI local heating and large-scale feedbacks.Previous data estimates of the global UHI, which considered the effect of urban areas but did not treat feedbacks or isolate temperature change due to urban surfaces from other causes of urban temperature change, imply a smaller UHI effect but of similar order. White roofs change surface albedo and affect energy demand. A worldwide conversion to white roofs, accounting for their albedo effect only, was calculated to cool population-weighted temperatures by ~0.02 K but to warm the Earth overall by ~0.07 K. White-roof local cooling may also affect energy use, thus emissions, a factor not accounted for here. As such, conclusions here regarding white roofs apply only to the assumptions made. 3 1.IntroductionUrban areas are generally warmer than vegetated areas around them since urban surfaces reduce evapotranspiration and have sufficiently different heat capacities, thermal conductivities, albedos, and emissivities to enhance urban warming [Howard, 1833;Oke, 1982]. Several studies have estimated, from data analysis, that the globally-averaged urban heat island (UHI) effect may contribute ≤0.1 K to global temperature changes since the preindustrial era [Jones, 1990;Easterling, 1997;Hansen et al., 1999;Peterson, 2003;Parker, 2006]. The IPCC Fourth Assessment Report concluded that the UHI may have increased temperatures ~0.065 over land and ~0.022 K globally from 1900-2008 [IPCC, 2007. The IPCC global estimate was scaled from the land estimate assuming no UHI heating or feedbacks over the ocean. Data analysis studies of the UHI do not account for feedbacks of changes in local temperatures, moisture, and their gradients to large-scale weather systems, either due to traceable effects or to deterministic chaotic variation. Furthermore, such studies cannot distinguish temperature changes in urban areas due to the UHI from those due to greenhouse gases, carbon dioxide domes over cities [Jacobson, 2010a], cooling or warming aerosol particles, transmission or use of electricity, stationary or mobile combustion, or human respiration, which also occur in urban areas. As such, numerical modeling is needed to ...

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Vertical mixing of commercial aviation emissions from cruise altitude to the surface

Cited by 28 publications

References 51 publications

Impacts of aircraft emissions on the air quality near the ground

Impacts of aircraft emissions on the air quality near the ground

The distribution of snow black carbon observed in the Arctic and compared to the GISS-PUCCINI model

Effects of Urban Surfaces and White Roofs on Global and Regional Climate

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